Fix: Add lifecycle management to AWQ linear function

csrc/layers/fused_linear.hpp

@@ -207,7 +207,7 @@ private:
 
 #define INFINILM_QKV_LINEAR_W4A16AWQ_INIT(name, q_name, k_name, v_name, ...)                                 \
     name##_ = std::make_shared<layers::QKVParallelLinear>(__VA_ARGS__);                                      \
-    auto awq_ptr = std::static_pointer_cast<infinicore::quantization::AWQ>(this->quantization_);             \
+    auto awq_ptr = std::static_pointer_cast<infinicore::quantization::AWQ>(name##_->get_quantization());     \
     int packing_num = awq_ptr->get_packing_num();                                                            \
     this->register_parameter(std::string(q_name) + ".qweight", name##_->get_q_weight_awq(packing_num));      \
     this->register_parameter(std::string(q_name) + ".qzeros", name##_->get_q_weight_zeros_awq(packing_num)); \

csrc/models/llama/llama_attention.cpp

@@ -112,12 +112,13 @@ LlamaAttention::LlamaAttention(std::shared_ptr<infinilm::config::ModelConfig> mo
                                   dtype, device, tp_rank, tp_size, rank_info.comm);
         break;
 
-    case infinicore::quantization::QuantScheme::AWQ_W4A16:
+    case infinicore::quantization::QuantScheme::AWQ_W4A16: {
         INFINILM_QKV_LINEAR_W4A16AWQ_INIT(qkv_proj, "q_proj", "k_proj", "v_proj", hidden_size_, head_dim_, model_config_->get<size_t>("num_attention_heads"), model_config_->get<size_t>("num_key_value_heads"), this->model_config_->get_quantization_method(), use_bias_,
                                           dtype, device, rank_info);
         INFINICORE_NN_MODULE_INIT(o_proj, model_config_->get<size_t>("num_attention_heads") * head_dim_, hidden_size_, this->model_config_->get_quantization_method(), use_output_bias_,
                                   dtype, device, tp_rank, tp_size, rank_info.comm);
         break;
+    }
     default:
         INFINILM_QKV_LINEAR_INIT(qkv_proj, "q_proj", "k_proj", "v_proj", hidden_size_, head_dim_, model_config_->get<size_t>("num_attention_heads"), model_config_->get<size_t>("num_key_value_heads"), this->model_config_->get_quantization_method(), use_bias_,
                                  dtype, device, rank_info);